Cameras and other photographic equipment produce digital images of landscapes, people, objects, and the like. Typically, a person identifies the content within each of the images, or compares the images to identify similarities or differences. Computerized systems perform edge detection or other techniques to automatically outline shapes within the images. Some of these computerized systems specifically outline faces within the images. The outlined faces are compared to images of known faces to identify the outlined faces. This comparison is referred to as face recognition. Face recognition is useful in, for example, traditional security and surveillance scenarios as well as in emerging online scenarios such as image tagging and image search. Existing face recognition algorithms, however, assume that the face images are very well aligned. This assumption is proven incorrect in real-life face recognition tasks, in which face detection and rectification have to be performed automatically prior to recognition. As such, the existing systems fail when attempting to perform face recognition on face images having significant pose variations.